Evidence map›Paper›PMID 34653374›Full record

Observational studyThe Lancet. Respiratory medicine2021

Longitudinal respiratory subphenotypes in patients with COVID-19-related acute respiratory distress syndrome: results from three observational cohorts.

Lieuwe D J Bos, Michael Sjoding, Pratik Sinha, Sivasubramanium V Bhavani, Patrick G Lyons, Alice F Bewley, Michela Botta, Anissa M Tsonas, Ary Serpa Neto, Marcus J Schultz and 3 more

Erratum issued Registry-linked trialOpen access · bronzeAbstract readMulticenter StudyObservational Study
In one paragraph

Observational study in The Lancet. Respiratory medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. It is linked to trial NCT04346342 (PRactice of VENTilation in COVID-19 Patients), which is not on this map. Cited by 80 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
80citing papers in PubMed, 1 pooled it
14.8field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT04346342 completednot on this map

PRactice of VENTilation in COVID-19 Patients (PRoVENT-COVID) - an Observational Study of Invasively Ventilated Patients in the Netherlands

TypeobservationalSponsorAcademisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA)Ran2020 to 2020Enrolled1,122ConditionsCOVID, Mechanical Ventilation, Acute Respiratory Failure
3 · Its place in the literature

Who cites it

80 citing papers in PubMed, 1 synthesis or guideline pooled it, 132 citations in OpenAlex.

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  18. The Impact of Inflammatory Biomarker Subphenotypes on Acute Respiratory Distress Syndrome Prognosis: A Systematic Review and Meta-analysis.Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2025
    Review
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20 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors at 3 institutions in 2 countries.

Lieuwe D J BosDepartment of Intensive Care and Laboratory of Experimental Intensive Care and Anaesthesiology (L·E·I·C·A), Amsterdam UMC, Amsterdam, Netherlands. Electronic address: l.d.bos@amsterdamumc.nl.
Michael SjodingDivision of Pulmonary and Critical Care Medicine, University of Michigan, Ann Arbor, MI, USA.
Pratik SinhaWashington University School of Medicine, St Louis, MO, USA.
Sivasubramanium V BhavaniDepartment of Medicine, University of Chicago, Chicago, IL, USA; Department of Medicine, Emory University, Atlanta, GA, USA.
Patrick G LyonsWashington University School of Medicine, St Louis, MO, USA.
Alice F BewleyWashington University School of Medicine, St Louis, MO, USA.
Michela BottaDepartment of Intensive Care and Laboratory of Experimental Intensive Care and Anaesthesiology (L·E·I·C·A), Amsterdam UMC, Amsterdam, Netherlands.
Anissa M TsonasDepartment of Intensive Care and Laboratory of Experimental Intensive Care and Anaesthesiology (L·E·I·C·A), Amsterdam UMC, Amsterdam, Netherlands.
Ary Serpa NetoDepartment of Intensive Care and Laboratory of Experimental Intensive Care and Anaesthesiology (L·E·I·C·A), Amsterdam UMC, Amsterdam, Netherlands; Australian and New Zealand Intensive Care Research Centre (ANZIC-RC), Monash University, Melbourne, VIC, Australia; Department of Critical Care Medicine, Hospital Israelita Albert Einstein, São Paulo, Brazil; Data Analytics Research and Evaluation (DARE) Centre, Austin Hospital and University of Melbourne, Melbourne, VIC, Australia.
Marcus J SchultzDepartment of Intensive Care and Laboratory of Experimental Intensive Care and Anaesthesiology (L·E·I·C·A), Amsterdam UMC, Amsterdam, Netherlands; Nuffield Department of Medicine, University of Oxford, Oxford, UK; Mahidol-Oxford Tropical Medicine Research Unit (MORU), Mahidol University, Bangkok, Thailand.
Robert P DicksonDivision of Pulmonary and Critical Care Medicine, University of Michigan, Ann Arbor, MI, USA.
Frederique PaulusDepartment of Intensive Care and Laboratory of Experimental Intensive Care and Anaesthesiology (L·E·I·C·A), Amsterdam UMC, Amsterdam, Netherlands.
PRoVENT-COVID collaborative group
Amsterdam University Medical Centers · NLWashington University in St. Louis · USUniversity of Michigan–Ann Arbor · US

Funding

Identification of Precision Sepsis Subphenotypes Using Vital Sign TrajectoriesK23GM144867 · NIGMS · EMORY UNIVERSITY · PI BHAVANI, SIVASUBRAMANIUM · 2021 to 2025
$890k
Data-Driven Identification of the Acute Respiratory Distress SyndromeK01HL136687 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI SJODING, MICHAEL WILLIAM · 2017 to 2021
$862k
NHLBI NIH HHS K01 HL136687NIGMS NIH HHS K23 GM144867
6 · The paper itself

Abstract

backgroundPatients with COVID-19-related acute respiratory distress syndrome (ARDS) have been postulated to present with distinct respiratory subphenotypes. However, most phenotyping schema have been limited by sample size, disregard for temporal dynamics, and insufficient validation. We aimed to identify respiratory subphenotypes of COVID-19-related ARDS using unbiased data-driven approaches.

methodsPRoVENT-COVID was an investigator-initiated, national, multicentre, prospective, observational cohort study at 22 intensive care units (ICUs) in the Netherlands. Consecutive patients who had received invasive mechanical ventilation for COVID-19 (aged 18 years or older) served as the derivation cohort, and similar patients from two ICUs in the USA served as the replication cohorts. COVID-19 was confirmed by positive RT-PCR. We used latent class analysis to identify subphenotypes using clinically available respiratory data cross-sectionally at baseline, and longitudinally using 8-hourly data from the first 4 days of invasive ventilation. We used group-based trajectory modelling to evaluate trajectories of individual variables and to facilitate potential clinical translation. The PRoVENT-COVID study is registered with ClinicalTrials.gov, NCT04346342.

findingsBetween March 1, 2020, and May 15, 2020, 1007 patients were admitted to participating ICUs in the Netherlands, and included in the derivation cohort. Data for 288 patients were included in replication cohort 1 and 326 in replication cohort 2. Cross-sectional latent class analysis did not identify any underlying subphenotypes. Longitudinal latent class analysis identified two distinct subphenotypes. Subphenotype 2 was characterised by higher mechanical power, minute ventilation, and ventilatory ratio over the first 4 days of invasive mechanical ventilation than subphenotype 1, but PaO

interpretationAt baseline, COVID-19-related ARDS has no consistent respiratory subphenotype. Patients diverged from a fairly homogenous to a more heterogeneous population, with trajectories of ventilatory ratio and mechanical power being the most discriminatory. Modelling these parameters alone provided prognostic value for duration of mechanical ventilation and mortality.

fundingAmsterdam UMC.

Indexed as

COVID-19Respiratory Distress SyndromeAgedCross-Sectional StudiesFemaleHumansIntensive Care UnitsMaleMiddle AgedNetherlandsProspective StudiesRespiration, ArtificialSARS-CoV-2

Identifiers

PMID34653374
PMCPMC8510633
OpenAlexW3205087455

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.